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Identification of handloom and powerloom fabrics using proximal support vector machines

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Title Statement Identification of handloom and powerloom fabrics using proximal support vector machines
 
Added Entry - Uncontrolled Name Ghosh, Anindya ; Government College of Engineering & Textile Technology, Berhampore, West Bengal-742 101
Guha, Tarit ; Government College of Engineering & Textile Technology, Berhampore, West Bengal-742 101
Bhar, R B; Department of Instrumentation, Jadavpur University, Kolkata, India-700 032
 
Uncontrolled Index Term Handloom fabrics; Image processing; Pattern classification; Proximal support vector machine; Powerloom fabrics
 
Summary, etc. <p class="abstract" style="text-align: justify;">This study endeavors to recognize handloom and powerloom products by means of proximal support vector machine (PSVM) using the features extracted from gray level images of both fabrics. A <em>k</em>-fold cross validation technique has been applied to assess the accuracy. The robustness, speed of execution, proven accuracy coupled with simplicity in algorithm hold the PSVM as a foremost classifier to recognize handloom and powerloom fabrics.</p><p> </p>
 
Publication, Distribution, Etc. Indian Journal of Fibre & Textile Research (IJFTR)
2015-04-20 15:30:18
 
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http://op.niscair.res.in/index.php/IJFTR/article/view/3809
 
Data Source Entry Indian Journal of Fibre & Textile Research (IJFTR); ##issue.vol## 40, ##issue.no## 1 (2015): Indian Journal of Fibre & Textile Research
 
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